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Temporal and instantaneous connectivity of default mode network estimated using Gaussian Bayesian network frameworks
Li, Juan1; Li, Rui5; Chen, Kewei1,3,4; Yao, Li1,2; Wu, Xia1,2; Wu, X (reprint author), Beijing Normal Univ, Coll Informat Sci & Technol, Xin Jie Kou Wai St 19, Beijing 100875, Peoples R China.
2012-03-28
发表期刊NEUROSCIENCE LETTERS
ISSN0304-3940
文章类型Article
卷号513期号:1页码:62-66
产权排序4
摘要By probing its functional anatomy, the default mode network (DMN) can be considered consisting of two interacting hub and non-hub subsystems. The hub subsystem includes posterior cingulate cortex (PCC), medial prefrontal cortex (MPFC) and bilateral inferior parietal cortex (IPC). The non-hub subsystem contains inferior temporal cortex (ITC) and (para) hippocampus (HC). In this study, Gaussian Bayesian Network (BN) and Gaussian Dynamic Bayesian Network (DBN) were applied separately to detect the instantaneous and temporal connection relationship within each and between the two DMN subsystems. It was found that the directional instantaneous interactions between the two subsystems were primarily "from non-hub to hub". The temporal interactions between hub and non-hub regions, on the other hand, are less presented between the two subsystems. The hub subsystem demonstrated both strong instantaneous and temporal interactions among the hub regions, while the non-hub regions were only strongly inter-connected instantaneously but temporally isolated with each other. In addition, one of the hub regions, PCC, appears to be a confluent node and important in the functional integration within the network. (c) 2012 Elsevier Ireland Ltd. All rights reserved.
关键词Default mode network (DMN) Effective connectivity Instantaneous connectivity Temporal connectivity Bayesian networks (BN) Posterior cingulate cortex (PCC)
学科领域Cognitive Neuroscience
收录类别SCI
语种英语
项目资助者National Natural Science Foundation of China [60931003, 60905063] ; Scientific Foundation of Institute of Psychology, Chinese Academy of Sciences [Y1CX251005]
项目简介Thanks to the anonymous reviewers for their insightful views and constructive suggestions on the model interpretation. This work was supported by the Key Program (No.60931003), General Program (No.60905063) of National Natural Science Foundation of China and Scientific Foundation of Institute of Psychology, Chinese Academy of Sciences (No. Y1CX251005).
WOS记录号WOS:000302512800013
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被引频次:5[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.psych.ac.cn/handle/311026/13278
专题中国科学院心理健康重点实验室
通讯作者Wu, X (reprint author), Beijing Normal Univ, Coll Informat Sci & Technol, Xin Jie Kou Wai St 19, Beijing 100875, Peoples R China.
作者单位1.Beijing Normal Univ, Coll Informat Sci & Technol, Beijing 100875, Peoples R China
2.Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China
3.Banner Alzheimers Inst BAI, Phoenix, AZ 85006 USA
4.Banner Good Samaritan PET Ctr, Phoenix, AZ 85006 USA
5.Chinese Acad Sci, Inst Psychol, Key Lab Mental Hlth, Ctr Aging Psychol, Beijing 100875, Peoples R China
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GB/T 7714
Li, Juan,Li, Rui,Chen, Kewei,et al. Temporal and instantaneous connectivity of default mode network estimated using Gaussian Bayesian network frameworks[J]. NEUROSCIENCE LETTERS,2012,513(1):62-66.
APA Li, Juan,Li, Rui,Chen, Kewei,Yao, Li,Wu, Xia,&Wu, X .(2012).Temporal and instantaneous connectivity of default mode network estimated using Gaussian Bayesian network frameworks.NEUROSCIENCE LETTERS,513(1),62-66.
MLA Li, Juan,et al."Temporal and instantaneous connectivity of default mode network estimated using Gaussian Bayesian network frameworks".NEUROSCIENCE LETTERS 513.1(2012):62-66.
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